
The Art of Swing: You Are a Slugger?
Wang Ma, Jingjuan Huang, Qiang Hu, Junjie Qiu, Leping Li
STATDS, SUSTech, Shenzhen, China
{12012424,12112847,12111214,12111831,12112627}@mail.sustech.edu.cn
Abstract
The objective of this project is to establish precise metrics that accurately assess
a player’s batting ability, while systematically eliminating extraneous influences
such as luck, defense, and field conditions. This report aims to summarize and
critically analyze the key aspects of the newly-proposed batting metrics by Stat-
cast, focusing on the proposed metrics and their implications for determining a
batter classification rule.
1 Introduction
Baseball, often referred to as America’s pastime, holds a unique position in the world of sports due to
its rich history and the intricate statistical analysis it enables. This sport’s complexity offers a fertile
ground for applying advanced statistical and machine learning techniques, making it an ideal subject
for data science projects. The objective of this report is to delve into the intricacies of evaluating
batting performance using modern metrics proposed by Major League Baseball’s Statcast system.
Context and Motivation. Evaluating a batter’s performance in baseball is challenging due to a myr-
iad of influencing factors such as luck, the defensive prowess of fielders, and the characteristics of
different ballparks. Traditional metrics like batting average and home runs provide a snapshot but
often fail to capture the complete picture of a player’s abilities. The need for more precise metrics is
paramount for both performance analysis and financial decisions, such as player salaries. This pro-
ject aims to establish precise metrics that accurately assess a player’s batting ability, systematically
eliminating extraneous influences such as luck, defense, and field conditions.
Advances in Baseball Analytics. Statcast, a state-of-the-art tracking technology, has revolutionized
baseball analytics by providing detailed measurements of player movements and actions on the field.
On May 13, Statcast introduced six key metrics to better quantify a batter’s abilities:
•
Bat Speed: The velocity of the bat as it moves through the hitting zone.
•
Fast-swing Rate: The frequency at which a batter can achieve high bat speed.
•
Squared-up Rate: The consistency with which a batter makes solid contact with the ball,
leading to optimal hitting outcomes.
•
Blast: A measure of the quality of contact, typically resulting in extra-base hits.
•
Swing Length: The distance the bat travels during a swing, affecting the timing and control
of the hit.
•
Swords: Instances where a batter is completely fooled by a pitch, often leading to weak
contact or misses.
Categorization of Batters. Our project also highlights the categorization of batters based on their
skills and performance. Batters are classified into various groups such as Sluggers, Elite Batters,
Contact Batters, and Weak Batters. Each category exhibits distinct characteristics:
37th Conference on Neural Information Processing Systems (NeurIPS 2023).